Public health surveillance in the US Department of Veterans Affairs: evaluation of the Praedico surveillance system

被引:5
|
作者
Lucero-Obusan, Cynthia [1 ]
Oda, Gina [1 ]
Mostaghimi, Anoshiravan [1 ]
Schirmer, Patricia [1 ]
Holodniy, Mark [1 ,2 ]
机构
[1] Vet Hlth Adm, US Dept Vet Affairs, Patient Care Serv, Publ Hlth Program Off, Palo Alto, CA 94304 USA
[2] Stanford Univ, Div Infect Dis & Geog Med, Stanford, CA 94305 USA
关键词
Big data; Health informatics; Public health; Surveillance; Syndromic surveillance; System evaluation; Electronic health records; Veterans; BIG DATA; INFLUENZA;
D O I
10.1186/s12889-022-12578-2
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background Early threat detection and situational awareness are vital to achieving a comprehensive and accurate view of health-related events for federal, state, and local health agencies. Key to this are public health and syndromic surveillance systems that can analyze large data sets to discover patterns, trends, and correlations of public health significance. In 2020, Department of Veterans Affairs (VA) evaluated its public health surveillance system and identified areas for improvement. Methods Using the Centers for Disease Control and Prevention (CDC) Guidelines for Evaluating Public Health Surveillance Systems, we assessed the ability of the Praedico Surveillance System to perform public health surveillance for a variety of health issues and evaluated its performance compared to an enterprise data solution (VA Corporate Data Warehouse), legacy surveillance system (VA ESSENCE) and a national, collaborative syndromic surveillance platform (CDC NSSP BioSense). Results Review of system attributes found that the system was simple, flexible, and stable. Representativeness, timeliness, sensitivity, and Predictive Value Positive were acceptable but could be further improved. Data quality issues and acceptability present challenges that potentially affect the overall usefulness of the system. Conclusions Praedico is a customizable surveillance and data analytics platform built on big data technologies. Functionality is straightforward, with rapid query generation and runtimes. Data can be graphed, mapped, analyzed, and shared with key decision makers and stakeholders. Evaluation findings suggest that future development and system enhancements should focus on addressing Praedico data quality issues and improving user acceptability. Because Praedico is designed to handle big data queries and work with data from a variety of sources, it could be enlisted as a tool for interdepartmental and interagency collaboration and public health data sharing. We suggest that future system evaluations include measurements of value and effectiveness along with additional organizations and functional assessments.
引用
收藏
页数:16
相关论文
共 50 条
  • [41] Development and validation of an automated emergency department-based syndromic surveillance system to enhance public health surveillance in Yukon: a lower-resourced and remote setting
    Bouchouar, Etran
    Hetman, Benjamin M.
    Hanley, Brendan
    BMC PUBLIC HEALTH, 2021, 21 (01)
  • [42] Carbon monoxide poisoning surveillance in the Veterans Health Administration, 2010–2017
    Gina Oda
    Russell Ryono
    Cynthia Lucero-Obusan
    Patricia Schirmer
    Mark Holodniy
    BMC Public Health, 19
  • [43] The Department of Veterans' Affairs Depleted Uranium Cohort in the Time of COVID-19 Translating a Traditional Surveillance Protocol to a Telehealth Platform
    McDiarmid, Melissa A.
    Hines, Stella
    Cloeren, Marianne
    Gucer, Patricia
    Condon, Marian
    Oliver, Marc
    Roth, Tracy
    Lewin-Smith, Michael R.
    Strathmann, Frederick
    Velez-Quinones, Maria A.
    Gaitens, Joanna M.
    JOURNAL OF OCCUPATIONAL AND ENVIRONMENTAL MEDICINE, 2023, 65 (08) : 670 - 676
  • [44] Development and validation of an automated emergency department-based syndromic surveillance system to enhance public health surveillance in Yukon: a lower-resourced and remote setting
    Etran Bouchouar
    Benjamin M. Hetman
    Brendan Hanley
    BMC Public Health, 21
  • [45] Preconception Health Indicators for Public Health Surveillance
    Robbins, Cheryl L.
    D'Angelo, Denise
    Zapata, Lauren
    Boulet, Sheree L.
    Sharma, Andrea J.
    Adamski, Alys
    Farfalla, Jennifer
    Stampfel, Caroline
    Verbiest, Sarah
    Kroelinger, Charlan
    JOURNAL OF WOMENS HEALTH, 2018, 27 (04) : 430 - 443
  • [46] Using Syndromic Surveillance for All-Hazards Public Health Surveillance: Successes, Challenges, and the Future
    Yoon, Paula W.
    Ising, Amy I.
    Gunn, Julia E.
    PUBLIC HEALTH REPORTS, 2017, 132 : 3S - 6S
  • [47] COVID-19 Insights Partnership: Leveraging big data from the Department of Veterans Affairs and supercomputers at the Department of Energy under the public health authority
    Ramoni, Rachel
    Klote, Molly
    Muralidhar, Sumitra
    Brandt, Cynthia
    Bernstein, Maya A.
    McMahon, Benjamin H.
    Jacobson, Daniel A.
    Justice, Amy C.
    JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2021, 28 (07) : 1578 - 1581
  • [48] Public Health Surveillance of CKD: Principles, Steps, and Challenges
    Powe, Neil R.
    Plantinga, Laura
    Saran, Rajiv
    AMERICAN JOURNAL OF KIDNEY DISEASES, 2009, 53 (03) : S37 - S45
  • [49] NextGen Public Health Surveillance and the Internet of Things (IoT)
    Sahu, Kirti Sundar
    Majowicz, Shannon E.
    Dubin, Joel A.
    Morita, Plinio Pelegrini
    FRONTIERS IN PUBLIC HEALTH, 2021, 9
  • [50] Early detection of influenza outbreaks using the DC Department of Health's syndromic surveillance system
    Griffin, Beth Ann
    Jain, Arvind K.
    Davies-Cole, John
    Glymph, Chevelle
    Lum, Garret
    Washington, Samuel C.
    Stoto, Michael A.
    BMC PUBLIC HEALTH, 2009, 9